Application of the Mean-shift Segmentation Parameters Estimator (MSPE) to VHSR satellite images: Tetuan-Morocco


  • O. Benarchid Ecole Nationale des Sciences Appliquées de Tétouan.
  • N. Raissouni Ecole Nationale des Sciences Appliquées de Tétouan.
  • J.A. Sobrino Universitat de València
  • A. El Ayyan Ecole Nationale des Sciences Appliquées de Tétouan.



MSPE, satellite, very high spatial resolution, Tetuan-Morocco


Image segmentation is considered as crucial step dealing with Object-Based Image Analysis (OBIA) and different segmentation results could be achieved by combining possible parameters values. Optimal parameters selection is usually carried out on the basis of visual interpretation; therefore, defining optimal combinations is a challenging task. In the present research, Mean-shift Segmentation Parameters estimator (MSPE) proposed tool is applied to automate the selection of segmentation parameters values to Very High Spatial Resolution (VHSR) satellite images in the region of Tetuan city (Northern Morocco). MSPE estimates the parameters values for the Mean-shift Segmentation (MS) algorithm. However, this algorithm needs as inputs: i) existing vector database and, ii) spectral data to define automatically the segmentation parameter values. Finally, application of the MSPE method on different landscape’ types show accurate results with Under-Segmentation (US) values ≤0.20 for industrial, residential and rural zones, while for dense residential area values of 0.35.


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Author Biographies

N. Raissouni, Ecole Nationale des Sciences Appliquées de Tétouan.


RSGIS Association.

J.A. Sobrino, Universitat de València

Unidad de Cambio Global, Laboratorio IPL, Parque Científico


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